single-rb.php

JRM Vol.17 No.3 pp. 269-276
doi: 10.20965/jrm.2005.p0269
(2005)

Paper:

Detection of Wet-Road Conditions from Images Captured by a Vehicle-Mounted Camera

Muneo Yamada*, Koji Ueda*, Isao Horiba*,
Shin Yamamoto**, and Sadayuki Tsugawa**

*Nagoya Electric Works Co., Ltd., 29-1 Shinoda, Miwa-cho, Ama-gun, Aichi 490-1294, Japan

**Meijo University, 1-501 Shiogamaguchi, Tenpaku-ku, Nagoya-shi, Aichi 468-8502, Japan

Received:
October 18, 2004
Accepted:
April 20, 2005
Published:
June 20, 2005
Keywords:
road condition, polarization, Human Centered ITS View Aid System, ITS, ASV
Abstract
This paper discusses the detection of wet-road conditions based on images captured by cameras on the rearview mirror of a vehicle. Based on properties associated with water on a road, detection was stable for daytime and nighttime conditions. Water is recognized on the road based on polarization properties from images. Field tests verified detectability on an expressway at an average 100km/h, with favorable results.
Cite this article as:
M. Yamada, K. Ueda, I. Horiba, S. Yamamoto, and S. Tsugawa, “Detection of Wet-Road Conditions from Images Captured by a Vehicle-Mounted Camera,” J. Robot. Mechatron., Vol.17 No.3, pp. 269-276, 2005.
Data files:
References
  1. [1] Supervised by Road Bureau, The Minstry of Land, Infrastructure and Transport, “ITS HAND BOOK,” Highway Industry Development Organization of Japan, 2002.
  2. [2] S. Tsugawa, S. Yamamoto, and S. Kato, “Human Centered ITS View Aid System: Concept and Procedure Studies,” Proceedings of 9th World Congress of ITS, Paper#0219 (CD-ROM), 2002.
  3. [3] M. Yamada, T. Oshima, K. Ueda, I. Horiba, and S. Yamamoto, “Study of a road surface condition detection technique in the Human Centered ITS View Aid System,” Proceedings of 9th World Congress of ITS, Paper#3603 (CD-ROM), 2002.
  4. [4] H. Mizuno, M. Yasuda, M. Itoh, S. Yamamoto, and S. Mori, “Measurement of the Driver’s Blinking and Estimation of their Awareness using the Image Processing,” Proceedings of 9th World Congress of ITS, Paper#3136 (CD-ROM), 2002.
  5. [5] H. Ishigaki, K. Katou, N. Miki, M. Kawasumi, and S. Yamamoto, “The Dispray Method of Route Information and Driver Support Information System Depending on the Degrees of the Consciousness of a Driver and Feature for the Elderly,” Proceedings of 9th World Congress of ITS, Paper#3085 (CD-ROM), 2002.
  6. [6] S. Tsugawa et al., “Demo 2000 Cooperative Driving: An Overview,” Proceedings of 8th World Congress of ITS, (CD-ROM), 2001.
  7. [7] T. Kuno, H. Sugiura, and J. Yoshida, “Detection of Road Condition with CCD Cameras Mounted on a Vehicle,” Trans. Inst. Electron. Inform. Commun. Eng. Japan, Vol.J81-D-II, No.10, pp. 2301-2310, 1998.
  8. [8] K. Ueda, I. Horiba, K. Ikegaya, and T. Ooi, “A Detecting Method of Wet Condition on Road Using Image Processing,” Trans. Inform. Process. Soc. Japan, Vol.35, No.6, pp. 1072-1080, 1994.
  9. [9] M. Yamada, T. Tanizaki, K. Ueda, I. Horiba, and N. Sugie, “A System of Discrimination of the Road Condition by means of Image Processing,” Trans. IEE of Japan, Vol.120-D, No.8/9, pp. 1053-1060, 2000.
  10. [10] M. Yamada, K. Ueda, I. Horiba, and N. Sugie, “Discrimination of the Road Condition Toward Understanding of Vehicle Driving Environments,” IEEE Trans. Intelligent Transportation Systems, Vol.2, No.1, pp. 26-31, 2001.
  11. [11] R. M. Haralick, K. Shanmugam, and I. Dinstein, “Texture Features for Image Classification,” IEEE Trans. Syst., Man, Cybern., Vol.SMC-3, No.6, pp. 610-621, 1973.
  12. [12] F. Murtagh, and A. Heck, “Multivariate Data Analysis,” Astrophysics and Space Science Library, Dordrecht, 1987.
  13. [13] A. Rosenfeld, and A. C. Kak, “Digital Picture Processing,” Academic Press, New York, 1976.
  14. [14] N. Otsu et al., “A Threshold Selection Method from Gray-level Histograms,” IEEE Trans. SMC-9, pp. 62-66, 1979.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 05, 2024